Concept and Methodologies

In line with the principles of the EUCloudEdgeIOT Initiative, MYRTUS Reference Iinfrastructure and MIRTO Cognitive Engine contribute to realise a seamless integration environment, including heterogeneous resources, while being compatible with already available infrastructures. The MYRTUS Design and Programming Environmentrepresents the instrument needed to design, deploy, and operate such a seamless and diverse continuum. The proposed technologies enable the emergence of CPS with a living dimension. A two-phase iterative approach of 18 months is followed to allow the assessment of the first version of MYRTUS technology and gather feedback from communities and stakeholders to improve results.

MYRTUS knowledge, data, and technology sharing


Open-source guarantees the support of the community built behind the technology and eases customizations and third-party extensions. Usage of open-source HW platforms and template architectures, definition of open-source functions and algorithms, and open-source tools and frameworks will facilitate MYRTUS results uptake.


MYRTUS provides an MLIR-based interoperability framework for node level optimization and code generation, facilitating system integration and easing migration among devices, as well as interoperability with third-party solutions (e.g., making the DPE compatible with other tools like PyTorch and TensorFlow). At the orchestration level, an ontological knowledge-based approach, leveraging standards, defines an interoperable hierarchy of distributed monitors and AI-powered managers allowing for cross-layer learning and information flow.


MYRTUS exploits containers-/Kubernetes-based solutions to support portability on already existing systems without changing completely the computing layers. This allows portability over legacy systems, supporting the use of existing infrastructure leveraging principles of the “sharing economy” and pursuing, in turn, sustainability.

Adherence to the sustainable and responsible computing paradigm


Supported by MYRTUS principle of openness, interoperability, and portability.

HW reconfiguration: Reconfigurable computing approaches and the use of FPGA-based HMPSoCs offer customization while keeping the benefits of general-purpose multicore tightly coupled to the reconfigurable logic. These platforms facilitate long-term maintenance and on-demand update using Over-The-Air-like approaches without changing the basic boards.

Legacy systems compliancy: Part of the MIRTO cognitive engine will be platform dependent, but the formalisation of the cognitive self-adaptation loop, provided as a template based on a set of reusable solutions, and the use of container-based and Kubernetes-based solutions eases implementation and solution porting also on legacy systems. Thanks to these, any substrate can be included or become a MYRTUS-compliant system.


Supported by HW specialisation and optimization techniques.

HW specialisation: MYRTUS provides: 1) template architectures for specialised run-time reconfigurable HW, to deploy HMPSoCs on FPGA; 2) adaptive processors with specialised accelerators integrated in their datapath, leveraging open and extensible computer architectures (i.e., RISC-V). Heterogeneity and specialisation are made transparent to programmers, through automatic and efficient SW-to-HW code offloading.

Optimization techniques: MYRTUS DPE will provide optimal workloads placement, featuring also HW-SW device-specific optimizations for figures such as energy consumption and performance. At runtime, MIRTO will provide 360° energy optimized orchestration, yielding higher energy efficiency of the cloud-edge system. Shifting services more towards fog/edge will also lower dependency on big data centres.

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MYRTUS is funded by the European Union, by grant No. 101135183. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.

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